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Learning management through matching : a field experiment using mechanism design

Author: Girum Abebe; Marcel Fafchamps; Michael Koelle; Simon Quinn; National Bureau of Economic Research,
Publisher: Cambridge, Mass. : National Bureau of Economic Research, 2019.
Series: Working paper series (National Bureau of Economic Research), no. 26035.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
What is the effect of exposing motivated youth to firm management in practice? To answer this question, we place young professionals for one month in established firms to shadow middle managers. Using random assignment into program participation, we find positive average effects on wage employment, but no average effect on the likelihood of self-employment. Within the treatment group, we match individuals and firms  Read more...
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Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Girum Abebe; Marcel Fafchamps; Michael Koelle; Simon Quinn; National Bureau of Economic Research,
OCLC Number: 1107991306
Notes: "July 2019"
Includes online appendix (56 pages).
Description: 1 online resource (44 pages) : illustrations.
Series Title: Working paper series (National Bureau of Economic Research), no. 26035.
Responsibility: Girum Abebe, Marcel Fafchamps, Michael Koelle, Simon Quinn.

Abstract:

What is the effect of exposing motivated youth to firm management in practice? To answer this question, we place young professionals for one month in established firms to shadow middle managers. Using random assignment into program participation, we find positive average effects on wage employment, but no average effect on the likelihood of self-employment. Within the treatment group, we match individuals and firms in batches using a deferred-acceptance algorithm. We show how this allows us to identify heterogeneous treatment effects by firm and intern. We find striking heterogeneity in self-employment effects, but almost no heterogeneity in wage employment. Estimates of marginal treatment effects (MTE) are then used to simulate counterfactual mechanism design. We find that some assignment mechanisms substantially outperform random matching in generating employment and income effects. These results demonstrate the importance of treatment heterogeneity for the design of field experiments and the role of matching algorithms in intervention design.

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